An updated Axiom buffalo genotyping array map and mapping of cattle quantitative trait loci to the new water buffalo reference genome assembly

2021 ◽  
Author(s):  
A. V. Nascimento ◽  
A. R. S. Romero ◽  
M. Y. Nawaz ◽  
D. F. Cardoso ◽  
D. J. A. Santos ◽  
...  
2020 ◽  
Author(s):  
Alia Parveen ◽  
Christa D. Jackson ◽  
Shatovisha Dey ◽  
Katy Tarrant ◽  
Nicholas B Anthony ◽  
...  

Abstract Background Ascites syndrome is a hypertensive, multifactorial, multigene trait affecting meat-type chickens imposing significant economic losses on the broiler industry. A region containing the CPQ gene has been previously identified as significantly affecting ascites phenotype. The region was discovered through whole genome resequencing focused on chicken chromosome 2. The association was confirmed through further genotyping in multiple broiler populations. Results The whole genome resequencing analyses have now been extended to the current chicken genome assembly. DNA samples were pooled according to gender and phenotype and the pools subjected to next generation sequencing. Loci were identified as clusters of single nucleotide polymorphisms where frequencies of the polymorphisms differed between resistant and susceptible chickens. The chickens are an unselected line descended from a commercial elite broiler line. Regions identified were specific to one or both genders. The data identify a total of 28 regions as potential quantitative trait loci for ascites. The genes from these regions have been associated with hypertensive-related traits in human association studies. One region on chicken chromosome 28 contains the LRRTM4 gene. Additional genotyping for the LRRTM4 region demonstrates an epistatic interaction with the CPQ region for ascites phenotype. Conclusions The 28 regions identified were not previously identified in a multi-generational genome wide association study using 60k Single Nucleotide Polymorphism panels. This work demonstrates the utility of whole genome resequencing as a cost effective, direct, and efficient method for identifying specific gene regions affecting complex traits. The approach is applicable to any organism with a genome assembly and requires no a priori assumptions.


2020 ◽  
Author(s):  
Alia Parveen ◽  
Christa Jackson ◽  
Shatovisha Dey ◽  
Katy Tarrant ◽  
Nicholas B Anthony ◽  
...  

Abstract Background Ascites syndrome is a hypertensive, multifactorial, multigene trait affecting meat-type chickens imposing significant economic losses on the broiler industry. A region containing the CPQ gene has been previously identified as significantly affecting ascites phenotype. The region was discovered through whole genome resequencing focused on chicken chromosome 2. The association was confirmed through further genotyping in multiple broiler populations. Results The whole genome resequencing analyses have now been extended to the current chicken genome assembly. DNA samples were pooled according to gender and phenotype and the pools subjected to next generation sequencing. Loci were identified as clusters of single nucleotide polymorphisms where frequencies of the polymorphisms differed between resistant and susceptible chickens. The chickens are an unselected line descended from a commercial elite broiler line. Regions identified were specific to one or both genders. The data identify a total of 28 regions as potential quantitative trait loci for ascites. The genes from these regions have been associated with hypertensive-related traits in human association studies. One region on chicken chromosome 28 contains the LRRTM4 gene. Additional genotyping for the LRRTM4 region demonstrates an epistatic interaction with the CPQ region for ascites phenotype. Conclusions The 28 regions identified were not previously identified in a multi-generational genome wide association study using 60k Single Nucleotide Polymorphism panels. This work demonstrates the utility of whole genome resequencing as a cost effective, direct, and efficient method for identifying specific gene regions affecting complex traits. The approach is applicable to any organism with a genome assembly and requires no a priori assumptions.


2012 ◽  
Vol 50 (08) ◽  
Author(s):  
R Hall ◽  
R Müllenbach ◽  
S Huss ◽  
R Alberts ◽  
K Schughart ◽  
...  

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